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Methods for Removing Dyes from Polluted Water; A Review
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Most of the water pollutants with dyes are leftovers from industries, including textiles, wool and others. There are many ways to remove dyes such as sorption, oxidation, coagulation, filtration, and biodegradation, Chlorination, ozonation, chemical precipitation, adsorption, electrochemical processes, membrane approaches, and biological treatment are among the most widely used technologies for removing colors from wastewater. Dyes are divided into two types: natural dyes and synthetic dyes.

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
A comparison of the Effects of Lemon Peel -Silver Nanoparticles Versus Brand Toothpastes and Mouthwashes on Staphylococcus Spp. Isolated From Teeth Caries
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Thirty one  samples of gum swabs were collected from patients with tooth caries (5-30 years old)  from the College of Science (Biology department )- University of Baghdad- Iraq for the period from October 2018 to December 2018. , The samples were transported, after inoculation in a transport media (nutrient broth), to the laboratory of the College of Science and then cultured on mannitol salt agar and  blood agar). The isolates belonging to Staphylococcus spp. were identified by biochemical tests and Vitek 2 compact system, while the more antibiotic resistant isolates were identified by using Polymerase Chain Reaction(ï´¾PCR)  and sequencing of 16SrRNA . The results showed sharp UV absorption peaks at 330 - 340nm and AFM at 5

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Publication Date
Wed Oct 09 2019
Journal Name
International Journal Of Drug Delivery Technology
The comparative study among the MRSAcin, Nisin A and vancomycin, on biofilm formation by Methicillin resistance Staphylococcus aureus isolated from food sources.
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Biofilms formation by pathogens microbial Control considered important in medical research because it is the hazarded virulence factor leading to becoming difficult to treat because of its high resistance to antimicrobials. Glycopeptide antibiotic a (Vancomycin) and the commercial bacteriocin (Nisin A) were used to comparative with purification bacteriocin (MRSAcin) against MRSA biofilm. One hundred food samples were collected from Baghdad markets from July 2016 to September 2016, including (cheese, yogurt, raw milk, fried meat, grilled meat, and beef burger). All samples were cultures; S. aureus was confirmation by macroscopic culture and microscopic examination, in addition to biochemical tests. Methicillin resistance S. asureus (

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Entomology And Zoology Studies
Isolation and identification of Enterococcus fecalis from cow milk samples and vaginal swab from
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The aim of the present study was to isolated the Enterococcus spp. from milk samples of cow and vaginal swabs from aborted women and patient women in Baghdad during September 2016 to april 2017. All 100 milk sample collecting was carried out on California Mastitis Test (CMT) and the positive Percentage of CMT reactions was 5% and the percentage of Enterococcus isolates from mastitic milk was 60% and 30% from nonmasitic milk. The prevalence of Enterococcus spp was 31% of milk samples and the prevalence of Enterococcus spp. Isolates were 67.74% of the isolates of cow milk samples were Enterococcus faecalis, 25.80% was Group D and 6.45% was non groupable while Enterococcus spp. isolates from aborted women samples were 20% and all isolated was

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Biotechnology Research Center
Determination the titer antibodies against LPS extracted from Pseudomonas aeruginosa isolated from eye infection
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Publication Date
Tue Oct 16 2018
Journal Name
International Journal Of Pharmaceutical Quality Assurance
Effects of Bacterocin from MRSA and Nigella Sativa (seed oil) against Biofilm from MRSA
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A many risk challenge in (settings hospital) are multi- bacteria are antibiotic-resistant. Some type strains that ability adhesion surface-attached bio-film census. Fifteen MRSA isolates were considered as high biofilm producers Moreover all MRSA isolates; M3, M5, M7 and M11 produced biofilms but the thickest biofilm seen M7strain. The MIC values of N. sativa oil against clinical isolates of MRSA were between (0.25, 0.5, 0.75, 1.0) μg/ml While MRSAcin (50, 75, 100, 125) µg\ ml. All biofilms treated with MRSAcin and Nigella sativa developed a presence of live cells after cultured on plate agar with inhibition zone between MIC (18 – 15) and (14- 11)mm respectively.Yet, results showed that MRSA supernatant developed a inhibitory ef

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

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Publication Date
Sat Jan 01 2022
Journal Name
Education For Health
Determinants of social accountability for medical schools in Iraq: A qualitative case study
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Publication Date
Fri Feb 26 2021
Journal Name
Life-cycle Civil Engineering: Innovation, Theory And Practice
Shear performance of a novel demountable connector for reusable steel-concrete composite structures
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A novel demountable shear connector is proposed to link a concrete slab to steel sections in a way that resulting steel-concrete composite floor is demountable, i.e. it can be easily dismantled at the end of its service life. The proposed connectors consist of two parts: the first part is a hollow steel tube with internal threads at its lower end. The second part is a compatible partially threaded bolted stud. After linking the stud to the steel section, the hollow steel tube can be fastened over the threaded stud, which create a complete demountable shear connector. The connector is suitable for use in both composite bridges and buildings, and using cast in-situ slabs, precast solid slabs, or hollow-core precast slabs. A series of push-off

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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